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Record W6989415362

Artful Encounters: Sites of Visual Inquiry

2021· book· en· W6989415362 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2021
Typebook
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsNexus (standard)Variety (cybernetics)Interpretation (philosophy)Contemporary artCreativityProduct (mathematics)Art methodologyMultidisciplinary approach
DOInot available

Abstract

fetched live from OpenAlex

Art collections are profound research environments. They steward the creative impulses of past and contemporary societies; provide sites for critical reflection on objects and their multifarious contexts; motivate productive dialogue between objects and beholders; and engage with and reflect upon the values that drive the creation, exchange, and interpretation of the manifestations of human imagination. In the summer of 2019, a workshop hosted by the University of Guelph’s Bachinski/Chu Print Study Collection in the School of Fine Art and Music brought together a multidisciplinary group to examine the contributions of collaborative, interdisciplinary programming that use works of art for purposes beyond the immediate study of art and culture. Art historians, artists, museum professionals, and their co-investigators from a variety of STEM disciplines, along with students and community partners, convened for this two-day event. This book provides the Nexus for Innovation workshop participants a venue through which to further explore and consider more deeply the roles art can play in stimulating multi- and interdisciplinary discourse and developing intellectual and observational competencies. The authors represented in this collection of essays shed light on the constitutive nature of art as both a product and agent of creative invention. The artful encounters examined here demonstrate how the spaces created to confront works of art become important sites of productive visual inquiry.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.257
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.239
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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